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arXiv 2104.08052cs.CV
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ScreenSeg: On-Device Screenshot Layout Analysis

OnDevice AI Samsung R\& D Institute Bangalore, India

Manoj Goyal, Rachit S Munjal, Sukumar Moharana, Deepak Garg, Debi Prasanna Mohanty, Siva Prasad Thota

英文摘要:

We propose a novel end-to-end solution that performs a Hierarchical Layout Analysis of screenshots and document images on resource constrained devices like mobilephones. Our approach segments entities like Grid, Image, Text and Icon blocks occurring in a screenshot. We provide an option for smart editing by auto highlighting these entities for saving or sharing. Further this multi-level layout analysis of screenshots has many use cases including content extraction, keyword-based image search, style transfer, etc. We have addressed the limitations of known baseline approaches, supported a wide variety of semantically complex screenshots, and developed an approach which is highly optimized for on-device deployment. In addition, we present a novel weighted NMS technique for filtering object proposals. We achieve an average precision of about 0.95 with a latency of around 200ms on Samsung Galaxy S10 Device for a screenshot of 1080p resolution. The solution pipeline is already commercialized in Samsung Device applications i.e. Samsung Capture, Smart Crop, My Filter in Camera Application, Bixby Touch.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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